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Description: BLS-GSM 即\"Bayesian Least Squares - Gaussian Scale Mixture\".基于贝叶斯最小平方-高斯概率混合模型的算法。用于图像去噪。相关文献索引详见readme
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Size: 1402073 |
Author: 戴宏斌 |
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Description: 基于BLS-GSM的图像去噪程序，在去噪的同时，能更多地保留图像的边缘和细节
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Size: 1401760 |
Author: 369446127@qq.com |
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Description: 随机信号处理中的经典去噪算法集合，有很多非常好的算法，值得研究。-Random signal processing Denoising Algorithm classic collection, there are many very good algorithms, is worth studying.
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Author: 牟建超 |
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Description: BLS-GSM 即"Bayesian Least Squares - Gaussian Scale Mixture".基于贝叶斯最小平方-高斯概率混合模型的算法。用于图像去噪。相关文献索引详见readme-BLS-GSM or
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Size: 1401856 |
Author: 戴宏斌 |
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Description: 现在在所有图像去噪滤波中最较理想的去噪算法——Bayesian Least Squares - Gaussian Scale Mixture的matlab实现代码，应用丰富，与商用图像处理软件媲美，其原理可以参见J Portilla, V Strela, M Wainwright, E P Simoncelli, "Image Denoising
using Scale Mixtures of Gaussians in the Wavelet Domain-Now image denoising filter in all the most better denoising algorithm- Bayesian Least Squares- Gaussian Scale Mixture realize the matlab code, application-rich, with the commercial image processing software rival, and its principle can be found in J Portilla, V Strela, M Wainwright, EP Simoncelli,
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Size: 1370112 |
Author: pudndcy |
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Description: 基于小波域隐马尔可夫模型的图像降噪，性能最好的图像降噪程序。
-Based on wavelet-domain Hidden Markov Model of image noise, the performance of the best image noise reduction procedures.
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Size: 1403904 |
Author: 蒲秀娟 |
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Description: Decompose image into subbands, denoise, and recompose again.
fh = decomp_reconst(im,Nsc,Nor,block,noise,parent,covariance,optim,sig)
covariance: are we considering covariance or just variance?
optim: for choosing between BLS-GSM (optim = 1) and MAP-GSM (optim = 0)
sig: standard deviation (scalar for uniform noise or matrix for spatially varying noise)
Version using the Full steerable pyramid (2) (High pass residual
splitted into orientations).
JPM, Univ. de Granada, 5/02
Last Revision: 11/04
- Decompose image into subbands, denoise, and recompose again.
fh = decomp_reconst(im,Nsc,Nor,block,noise,parent,covariance,optim,sig)
covariance: are we considering covariance or just variance?
optim: for choosing between BLS-GSM (optim = 1) and MAP-GSM (optim = 0)
sig: standard deviation (scalar for uniform noise or matrix for spatially varying noise)
Version using the Full steerable pyramid (2) (High pass residual
splitted into orientations).
JPM, Univ. de Granada, 5/02
Last Revision: 11/04
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Size: 1024 |
Author: ali |
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Description:
Decompose image into subbands, denoise using BLS-GSM method, and recompose again.
fh = decomp_reconst(im,Nsc,filter,block,noise,parent,covariance,optim,sig)
im: image
Nsc: number of scales
filter: type of filter used (see namedFilters)
block: 2x1 vector indicating the dimensions (rows and columns) of the spatial neighborhood
noise: signal with the same autocorrelation as the noise
parent: include (1) or not (0) a coefficient from the immediately coarser scale in the neighborhood
covariance: are we considering covariance or just variance?
optim: for choosing between BLS-GSM (optim = 1) and MAP-GSM (optim = 0)
sig: standard deviation (scalar for uniform noise or matrix for spatially varying noise)
Version using a critically sampled pyramid (orthogonal wavelet), as implemented in MatlabPyrTools (Eero).
JPM, Univ. de Granada, 3/03-
Decompose image into subbands, denoise using BLS-GSM method, and recompose again.
fh = decomp_reconst(im,Nsc,filter,block,noise,parent,covariance,optim,sig)
im: image
Nsc: number of scales
filter: type of filter used (see namedFilters)
block: 2x1 vector indicating the dimensions (rows and columns) of the spatial neighborhood
noise: signal with the same autocorrelation as the noise
parent: include (1) or not (0) a coefficient from the immediately coarser scale in the neighborhood
covariance: are we considering covariance or just variance?
optim: for choosing between BLS-GSM (optim = 1) and MAP-GSM (optim = 0)
sig: standard deviation (scalar for uniform noise or matrix for spatially varying noise)
Version using a critically sampled pyramid (orthogonal wavelet), as implemented in MatlabPyrTools (Eero).
JPM, Univ. de Granada, 3/03
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Size: 1024 |
Author: ali |
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Description: Decompose image into subbands (undecimated wavelet), denoise, and recompose again.
fh = decomp_reconst_wavelet(im,Nsc,daub_order,block,noise,parent,covariance,optim,sig)
im : image
Nsc: Number of scales
daub_order: Order of the daubechie fucntion used (must be even).
block: size of neighborhood within each undecimated subband.
noise: image having the same autocorrelation as the noise (e.g., a delta, for white noise)
parent: are we including the coefficient at the central location at the next coarser scale?
covariance: are we considering covariance or just variance?
optim: for choosing between BLS-GSM (optim = 1) and MAP-GSM (optim = 0)
sig: standard deviation (scalar for uniform noise or matrix for spatially varying noise)
Javier Portilla, Univ. de Granada, 3/03
Revised: 11/04 - Decompose image into subbands (undecimated wavelet), denoise, and recompose again.
fh = decomp_reconst_wavelet(im,Nsc,daub_order,block,noise,parent,covariance,optim,sig)
im : image
Nsc: Number of scales
daub_order: Order of the daubechie fucntion used (must be even).
block: size of neighborhood within each undecimated subband.
noise: image having the same autocorrelation as the noise (e.g., a delta, for white noise)
parent: are we including the coefficient at the central location at the next coarser scale?
covariance: are we considering covariance or just variance?
optim: for choosing between BLS-GSM (optim = 1) and MAP-GSM (optim = 0)
sig: standard deviation (scalar for uniform noise or matrix for spatially varying noise)
Javier Portilla, Univ. de Granada, 3/03
Revised: 11/04
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Author: ali |
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Description: 去噪算法matlab源码三合一，包含BLS-GSM，BM3D，NLM-Denosing algorithms 3 in 1, include BLS-GSM+ BM3D+ NLM
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Size: 6711296 |
Author: deqiang |
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Description: 程序实现了三种去噪算法：BLS-GSM/BM3D/NLM，评价指标为PSNR/SSIM.-Program implements three de-noising algorithm: BLS-GSM/BM3D/NLM, with evaluation of PSNR/SSIM.
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Size: 8381440 |
Author: df |
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Description:
BLS-GSM代表“Bayesian Least Squares - Gaussian Scale Mixture(贝叶斯最小二乘-高斯尺度混合模型)”。
这个工具箱实现了该篇论文中介绍的算法：
J Portilla, V Strela, M Wainwright, E P Simoncelli, Image Denoising
using Scale Mixtures of Gaussians in the Wavelet Domain, IEEE
Transactions on Image Processing. vol 12, no. 11, pp. 1338-1351,
November 2003
这个工具箱进行图像去噪时，假定噪声类型为高斯噪声并且我们知道它的功率谱密度（不需要是白色的）。-BLS-GSM stands for Bayesian Least Squares- Gaussian Scale Mixture .
This toolbox implements the algorithm described in:
J Portilla, V Strela, M Wainwright, E P Simoncelli, Image Denoising
using Scale Mixtures of Gaussians in the Wavelet Domain, IEEE
Transactions on Image Processing. vol 12, no. 11, pp. 1338-1351,
November 2003
This
tool implements image denoising assuming that the noise is Gaussian,
and that we know its power spectral density (it does not need to be white).
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Size: 999424 |
Author: 沙天飞 |
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Description: BLS_GSM算法的matlab版源代码，实现图像去噪，去噪效果非常好，程序完整，能运行-BLS GSM algorithm matlab version of the source code to achieve denoising, denoising effect is very good, complete procedures, can run
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Size: 500736 |
Author: 刘宁宁 |
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